We live in a world reshaped by big data and smart digital technologies that scale with ever-decreasing marginal cost. But, to date, too little attention has been given to understanding the implications of this for learning, or to setting out the ways in which artificial intelligence (AI) can be used to create learning tools that are more efficient, flexible and inclusive than those currently available; tools that will help learners prepare for an economy that is swiftly being reshaped by digital technologies. In this important new report, a positive and plausible vision is set out of how learning could be transformed by artificial intelligence in education (AIEd). For example, technology available today could be applied to support student learning at a scale previously unimaginable by providing one-on-one tutoring to every student, in every subject. Existing technologies also have the capacity to provide intelligent support to learners working in a group, and to create authentic virtual learning environments where students have the right support, at the right time, to tackle real-life problems and puzzles.

Many are claiming that we are in the era of automation. Discussions around the self-driving car are heating up, IBM Watson is making headway, and the Internet of Things is making quite the splash in all aspects of our lives, from the smart home to smart cities. But what is automation's role in the workplace? A recent report from McKinsey and Company says that nearly half of work activities "could be automated using already demonstrated technology." With more businesses looking to adopt advanced tools that increase efficiency, the real value is still in the hands of humans, which hold the key in the form of decision making.

Want to know how much you spent on Uber rides last month? A new banking bot called MyKAI can give you some answers. Kasisto's new banking smart bot, which works with messaging platforms like Facebook Messenger and Slack to make financial transactions and answer questions, is part of a broader trend towards using AI to enrich customers' interactions with companies. You can make payments, ask the bot things like how much money is in your account, and even ask general questions like "What is a CD?" It can even provide an answer if you want to know if you have a gambling problem. But how does MyKAI fit into the bigger bot world? How is it using AI to enable meaningful conversations with customers?

For the human eye reading a CV (resume) or a job ad is an easy task. These semi-structured documents are usually separated in sections and have layouts that makes it easy to quickly identify important information. In contrast, a computer system that parses CVs needs to be continuously trained and adapted to deal with the endless expressivity of human language. As a leader in the field of language technology, Textkernel is working hard to provide the best CV parser to our customers. In this blog article I will explain how we achieve this and discuss the focus of our current research efforts.

Being able to make near-real-time decisions becomes increasingly crucial. To succeed, we need machine learning systems that can turn massive amounts of data into valuable insights. But when you're just starting out in the data science field, how do you get started creating machine learning applications? The answer is TensorFlow, a new open source machine learning library from Google that they use in their own successful products like Search, Maps, YouTube, Translate, and Photos. The TensorFlow library can take your high level designs and turn them into the low level mathematical operations required by machine learning algorithms.

The hitch reflects a much bigger technological challenge facing China's manufacturers today. Wages in Shanghai have more than doubled in the past seven years, and the company that owns the factory, Cambridge Industries Group, faces fierce competition from increasingly high-tech operations in Germany, Japan, and the United States. Last year the government of Guangdong, a province that contains many large manufacturing operations, promised to spend 150 billion equipping factories with industrial robots and creating two new centers dedicated to advanced automation. Despite the challenges, Day Chia-peng, general manager of Foxconn's automation technology development committee, says the company is automating a growing number of tasks on its lines.

As a part of this initiative, the Federal Government is working to leverage AI for public good and to aid in promoting more effective government. OSTP is in the process of co-hosting four public workshops in 2016 on topics in AI in order to spur public dialogue on these topics and to identify challenges and opportunities related to this emerging technology. These topics include the legal and governance issues for AI, AI for public good, safety and control for AI, and the social and economic implications of AI. A new National Science and Technology Council (NSTC) Subcommittee on Machine Learning and Artificial Intelligence has also been established. This group will monitor state-of-the-art advances and technology milestones in artificial intelligence and machine learning within the Federal Government, in the private sector, and internationally, as well as help coordinate Federal activity in this space.

So how does this work? Each bottle of beer has instructions to a website that asks visitors a series of questions. The answers to the questions are then sent to ABI. ABI then uses that feedback to make modifications to the ingredients for the next batch of beer. IntelligentX has had tech event attendees in and around London try their beers.

Over a couple of drinks, you cover the usual suspects: favourite foods, dream jobs, where you each grew up. On the way home, you wonder: Were they into me? They were smiling a lot, so probably. But they also looked at their watch a few times, so probably not. Now imagine that the whole time you two were talking, scientists were sitting under the table transcribing the conversation.

Microsoft has made Project Malmo, a platform that uses the world of Minecraft as a testing ground for advanced artificial intelligence research, available for novice to experienced programmers on GitHub via an open-source license. The system, which had until now only been open to a small group of computer scientists in private preview, is primarily designed to help researchers develop sophisticated, more general artificial intelligence, or AI, that can do things like learn, hold conversations, make decisions and complete complex tasks. That's key to creating systems that can augment human intelligence -- and eventually help us with everything from cooking and doing laundry to driving and performing lifesaving tasks in an operating room. Katja Hofmann, a researcher in Microsoft's Cambridge, UK, research lab, who leads the development of Project Malmo, said the system will help researchers develop new techniques and approaches to reinforcement learning. That's an area of AI in which agents learn how to complete a task by being given a lot of room for trial and error and then being rewarded when they make the right decision.